Lateral specialization in unilateral spatial neglect : a cognitive robotics model

CONTI, Daniela, DI NUOVO, Santo, CANGELOSI, Angelo and DI NUOVO, Alessandro (2016). Lateral specialization in unilateral spatial neglect : a cognitive robotics model. Cognitive Processing, 17 (3), 321-328.

art%3A10.1007%2Fs10339-016-0761-x.pdf - Published Version
Available under License Creative Commons Attribution.

Download (831kB) | Preview
Official URL:
Link to published version:: 10.1007/s10339-016-0761-x


In this paper, we present the experimental results of an embodied cognitive robotic approach for modelling the human cognitive deficit known as unilateral spatial neglect (USN). To this end, we introduce an artificial neural network architecture designed and trained to control the spatial attentional focus of the iCub robotic platform. Like the human brain, the architecture is divided into two hemispheres and it incorporates bio-inspired plasticity mechanisms, which allow the development of the phenomenon of the specialization of the right hemisphere for spatial attention. In this study, we validate the model by replicating a previous experiment with human patients affected by the USN and numerical results show that the robot mimics the behaviours previously exhibited by humans. We also simulated recovery after the damage to compare the performance of each of the two hemispheres as additional validation of the model. Finally, we highlight some possible advantages of modelling cognitive dysfunctions of the human brain by means of robotic platforms, which can supplement traditional approaches for studying spatial impairments in humans.

Item Type: Article
Research Institute, Centre or Group: Cultural Communication and Computing Research Institute > Communication and Computing Research Centre
Identification Number: 10.1007/s10339-016-0761-x
Related URLs:
Depositing User: Alessandro Di Nuovo
Date Deposited: 06 Sep 2016 08:47
Last Modified: 19 Oct 2016 23:27

Actions (login required)

View Item View Item


Downloads per month over past year

View more statistics